Dryness stress can limit vegetation growth and is often characterized by low soil moisture (SM) and high atmospheric water demand (vapor pressure deficit, VPD). However, the relative role of SM and VPD in limiting ecosystem production remains debated and is difficult to disentangle, as SM and VPD are coupled through land-atmosphere interactions, hindering the ability to predict ecosystem responses to dryness. Here, we combine satellite observations of solar-induced fluorescence with estimates of SM and VPD and show that SM is the dominant driver of dryness stress on ecosystem production across more than 70% of vegetated land areas with valid data. Moreover, after accounting for SM-VPD coupling, VPD effects on ecosystem production are much smaller across large areas. We also find that SM stress is strongest in semi-arid ecosystems. Our results clarify a longstanding question and open new avenues for improving models to allow a better management of drought risk.

Climate change modulates both energy demand and wind and solar energy supply but a globally synthetic analysis of supply–demand match (SDM) is lacking. Here, we use 12 state-of-the-art climate models to assess climate change impacts on SDM, quantified by the fraction of demand met by local wind or solar supply. For energy systems with varying dependence on wind or solar supply, up to 32% or 44% of non-Antarctic land areas, respectively, are projected to experience robust SDM reductions by the end of this century under an intermediate emission scenario. Smaller and more variable supply reduces SDM at northern middle-to-high latitudes, whereas reduced heating demand alleviates or reverses SDM reductions remarkably. By contrast, despite supply increases at low latitudes, raised cooling demand reduces SDM substantially. Changes in climate extremes and climate mean make size-comparable contributions. Our results provide early warnings for energy sectors in climate change adaptation.

Memory effects refer to the impacts of antecedent climate conditions on current vegetation productivity. This temporal linkage has been found to be strong in arid and semi-arid regions. However, the dominant climatic factors that determine such patterns are still unclear. Here, we defined’water-memory effects’ as the persistent effects of antecedent precipitation on the vegetation productivity for a given memory length (from 1 to up to 12 months). Based on satellite observations and climate data, we quantified the length of water-memory effects and evaluated the contributions of antecedent precipitation on current vegetation. Our results showed that vegetation productivity was highly dependent on antecedent precipitation in arid and semi-arid regions. The average length of water memory was approximately 5.6 months. Globally, water-memory effects could explain the geographical pattern and strength of memory effects, indicating that precipitation might be the dominant climatic factor determining memory effects because of its impact on water availability. Moreover, our results showed vegetation in regions with low mean annual precipitation or a longer water memory has lower engineering resilience (i.e. slower recovery rate) to disturbances. These findings will enable better assessment of memory effects and improve our understanding of the vulnerability of vegetation to climate change.